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\hyphenation{frame-shifts gen-bank da-ta-base hy-bri-di-za-tion}

\newcommand{\BWFtitle}[1]{A Computational Model for Translational
  Efficiency and Frameshifts in #1{Escherichia coli} Using a Genetic Signal
  Processing Approach}
\newcommand{\BWFauthors}{Vivek Bhattacharya, Hao Lian, and Daniel
  R. Vitek}

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\author{\BWFauthors}
\title{Abstract}

\begin{document}
\maketitle
In modern genetics, \ecoli\ is used as an expression system to commercially 
produce proteins.  However, sequence-dependent features, such as rare codons 
and codon bias, have large effects on translational efficiency.  To tackle 
this problem, we proposed a stochastic model to computationally estimate 
translational efficiency and predict frameshifting, uniting ideas from biological 
literature and developing two metrics with considerable predictive power 
for translational efficiency. We ran our model on 4364 sequences from the 
\ecoli\ genome and found over 90\% of them to have predicted high yields; 
moreover, the model predicts ribosomal proteins to translate at even higher rates---both 
results that concur with experimental evidence.  We investigated a set of eight 
sequences of recombinant bovine growth hormone, and the model correctly determined 
high or low levels of translation for seven of them.  We then examined variations of
\prfB, a gene with a programmed frameshift, and the model grouped these sequences 
into two general categories of high and low yield, consistent 
with experimental results.  Successful development of a computational model and 
metrics for translational efficiency implicates itself in optimizing 
recombinant protein yield in multiple fields, including commercial protein synthesis.
\end{document}
